Robotics
Transformers
ONNX
Safetensors
PyTorch
mvae
feature-extraction
prosoro
multimodal
custom_code
Instructions to use prosoro/prosoro-mvae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prosoro/prosoro-mvae with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("prosoro/prosoro-mvae", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3faded29fe06fccfafb12dedee89e50ee685eacbf1a85157885089f7e8ac7635
- Size of remote file:
- 8.23 MB
- SHA256:
- 38eb081d3c33db1f7b59b788ea8001f25c5a22aa0293f23d70f5421b4aa1e185
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